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      SERPINA1 methylation and lung function in tobacco-smoke exposed European children and adults: a meta-analysis of ALEC population-based cohorts

      , 1 , 2 , 1 , 2 , 3 , 4 , 4 , 5 , 1 , 2 , 1 , 2 , 6 , 7 , 8 , 6 , 9 , 10 , 4 , 6 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 16 , 17 , 18 , 16 , 17 , 16 , 4 , 6 , 9 , 19 , 20 , 5 , 3 , , 1 , 2

      Respiratory Research

      BioMed Central

      Chronic obstructive pulmonary disease; SERPINA1 methylation, DNA methylation, Epigenetics, Population based study, Smoking, Alpha-1 antitrypsin

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          The pathophysiological role of SERPINA1 in respiratory health may be more strongly determined by the regulation of its expression than by common genetic variants. A family based study of predominantly smoking adults found methylation at two Cytosine-phosphate-Guanine sites (CpGs) in SERPINA1 gene to be associated with chronic obstructive pulmonary disease risk. The objective of this study was to confirm the association of lung function with SERPINA1 methylation in general population samples by testing a comprehensive set of CpGs in the SERPINA gene cluster. We considered lung function level and decline in adult smokers from three European population-based cohorts and lung function level and growth in tobacco-smoke exposed children from a birth cohort.


          DNA methylation using Illumina Infinium Human Methylation 450 k and EPIC beadchips and lung function were measured at two time points in 1076 SAPALDIA, ECRHS and NFBC adult cohort participants and 259 ALSPAC children. Associations of methylation at 119 CpG sites in the SERPINA gene cluster ( PP4R4-SERPINA13P) with lung functions and circulating alpha-1-antitripsin (AAT) were assessed using multivariable cross-sectional and longitudinal regression models.


          Methylation at cg08257009 in the SERPINA gene cluster, located 32 kb downstream of SERPINA1, not annotated to a gene, was associated with FEV 1/FVC at the Bonferroni corrected level in adults, but not in children. None of the methylation signals in the SERPINA1 gene showed associations with lung function after correcting for multiple testing.


          The results do not support a role of SERPINA1 gene methylation as determinant of lung function across the life course in the tobacco smoke exposed general population exposed.

          Electronic supplementary material

          The online version of this article (10.1186/s12931-018-0850-8) contains supplementary material, which is available to authorized users.

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          Most cited references 16

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          Chronic obstructive pulmonary disease in non-smokers.

          Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. Tobacco smoking is established as a major risk factor, but emerging evidence suggests that other risk factors are important, especially in developing countries. An estimated 25-45% of patients with COPD have never smoked; the burden of non-smoking COPD is therefore much higher than previously believed. About 3 billion people, half the worldwide population, are exposed to smoke from biomass fuel compared with 1.01 billion people who smoke tobacco, which suggests that exposure to biomass smoke might be the biggest risk factor for COPD globally. We review the evidence for the association of COPD with biomass fuel, occupational exposure to dusts and gases, history of pulmonary tuberculosis, chronic asthma, respiratory-tract infections during childhood, outdoor air pollution, and poor socioeconomic status.
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            Complete pipeline for Infinium(®) Human Methylation 450K BeadChip data processing using subset quantile normalization for accurate DNA methylation estimation.

            Huge progress has been made in the development of array- or sequencing-based technologies for DNA methylation analysis. The Illumina Infinium(®) Human Methylation 450K BeadChip (Illumina Inc., CA, USA) allows the simultaneous quantitative monitoring of more than 480,000 CpG positions, enabling large-scale epigenotyping studies. However, the assay combines two different assay chemistries, which may cause a bias in the analysis if all signals are merged as a unique source of methylation measurement. We confirm in three 450K data sets that Infinium I signals are more stable and cover a wider dynamic range of methylation values than Infinium II signals. We evaluated the methylation profile of Infinium I and II probes obtained with different normalization protocols and compared these results with the methylation values of a subset of CpGs analyzed by pyrosequencing. We developed a subset quantile normalization approach for the processing of 450K BeadChips. The Infinium I signals were used as 'anchors' to normalize Infinium II signals at the level of probe coverage categories. Our normalization approach outperformed alternative normalization or correction approaches in terms of bias correction and methylation signal estimation. We further implemented a complete preprocessing protocol that solves most of the issues currently raised by 450K array users. We developed a complete preprocessing pipeline for 450K BeadChip data using an original subset quantile normalization approach that performs both sample normalization and efficient Infinium I/II shift correction. The scripts, being freely available from the authors, will allow researchers to concentrate on the biological analysis of data, such as the identification of DNA methylation signatures.
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              The European Community Respiratory Health Survey: what are the main results so far? European Community Respiratory Health Survey II.

              The European Community Respiratory Health Survey (ECRHS) was the first study to assess the geographical variation in asthma and allergy in adults using the same instruments and definitions. The database of the ECRHS includes information from approximately 140,000 individuals from 22 countries. The aim of this review is to summarize the results of the ECRHS to date. The ECRHS has shown that there are large geographical differences in the prevalence of asthma, atopy and bronchial responsiveness, with high prevalence rates in English speaking countries and low prevalence rates in the Mediterranean region and Eastern Europe. Analyses of risk factors have highlighted the importance of occupational exposure for asthma in adulthood. The association between sensitization to individual allergens and bronchial responsiveness was strongest for indoor allergens (mite and cat). Analysis of treatment practices has confirmed that the treatment of asthma varies widely between countries and that asthma is often undertreated. In conclusion, the European Community Respiratory Health Survey has shown that the prevalence of asthma varies widely. The fact that the geographical pattern is consistent with the distribution of atopy and bronchial responsiveness supports the conclusion that the geographical variations in the prevalence of asthma are true and most likely due to environmental factors.

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                Respir Res
                Respir. Res
                Respiratory Research
                BioMed Central (London )
                22 August 2018
                22 August 2018
                : 19
                [1 ]ISNI 0000 0004 0587 0574, GRID grid.416786.a, Swiss Tropical and Public Health Institute, ; Socinstrasse 57, 4002 Basel, Switzerland
                [2 ]ISNI 0000 0004 1937 0642, GRID grid.6612.3, University of Basel, ; Basel, Switzerland
                [3 ]ISNI 0000 0004 1936 9297, GRID grid.5491.9, Human Development and Health, Faculty of Medicine, , University of Southampton, ; Southampton, UK
                [4 ]ISNI 0000 0001 2113 8111, GRID grid.7445.2, Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, ; W2 1PG, London, UK
                [5 ]ISNI 0000 0001 2113 8111, GRID grid.7445.2, Population Health and Occupational Disease, NHLI, Imperial College London, ; London, UK
                [6 ]ISNI 0000 0001 0941 4873, GRID grid.10858.34, Center for Life Course Health Research, , University of Oulu, ; Oulu, Finland
                [7 ]Oulunkaari Health Center, Ii, Finland
                [8 ]Medical Research Center, University Hospital of Oulu, University of Oulu, Oulu, Finland
                [9 ]ISNI 0000 0001 0941 4873, GRID grid.10858.34, Biocenter Oulu, , University of Oulu, ; Oulu, Finland
                [10 ]ISNI 0000 0001 2113 8111, GRID grid.7445.2, Department for Genomics of Common Diseases, School of Public Health, Imperial College London, ; London, UK
                [11 ]Lungenpraxis Aarau, Hirslanden Klinik, Aarau, Switzerland
                [12 ]Zürcher Höhenklinik, Wald, Switzerland
                [13 ]ISNI 0000 0004 0514 9998, GRID grid.417053.4, Ospedale Regionale di Lugano-Sede Civico, ; Lugano, Switzerland
                [14 ]Clinic of Pulmonary Medicine and Respiratory Cell Research, Basel, Switzerland
                [15 ]ISNI 0000 0000 8853 2677, GRID grid.5361.1, Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, , Innsbruck Medical University, ; Innsbruck, Austria
                [16 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, MRC Integrative Epidemiology Unit, , University of Bristol, ; Bristol, UK
                [17 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, Department of Population Health Sciences, Bristol Medical School, , University of Bristol, ; Bristol, UK
                [18 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, Bristol Dental School, , University of Bristol, ; Bristol, UK
                [19 ]ISNI 0000 0004 4685 4917, GRID grid.412326.0, Unit of Primary Health Care, , Oulu University Hospital, OYS, ; Kajaanintie 50, 90220 Oulu, Finland
                [20 ]ISNI 0000 0001 0724 6933, GRID grid.7728.a, Department of Life Sciences, College of Health and Life Sciences, , Brunel University London, ; Kingston Lane, Uxbridge, Middlesex UB8 3PH UK
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

                Funded by: FundRef, Horizon 2020 Framework Programme;
                Award ID: No. 633212
                Award Recipient :
                Funded by: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (CH)
                Award ID: grants no 33CS30148470/1&2, 33CSCO134276/1, 33CSCO108796, , 324730_135673, 3247BO104283, 3247BO104288, 3247BO104284, 3247065896, 3100059302, 3200052720, 3200042532, 4026028099, PMPDP3_129021/1, PMPDP3_141671/1
                Award Recipient :
                Funded by: Ministère de la Santé (TN)
                Award ID: 90MR/10, 91AF/6
                Funded by: Academy of Finland (FI)
                Award ID: project grants 104781, 120315, 129269, 1114194, 24300796, 85547
                Funded by: University of Bristol (GB)
                Award ID: MC_UU_12013_2, MC_UU_12013_5 and MC_UU_12013_8
                Funded by: UK Biotechnology and Biological Sciences Research Council
                Award ID: BB/I025751/1 and BB/I025263/1
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